基于神经网络与图像处理的花生仁霉变识别方法

为了采用机器视觉对霉变花生仁的自动识别与分选，研究了一种基于花生仁图像特征和人工神经网络的霉变识别方法。首先，利用Sobel算子直接对噪声含量少、边缘保存较完整的B分量灰度图进行边缘检测，经过形态学滤波、填充、合成等处理去除背景，得到分割后的彩色花生仁图像。然后提取颜色特征H、I、S及纹理特征RW、GW、BW，将其作为MATLAB所创建的神经网络的输入，并分别定义正常、轻度霉变、严重霉变3组代码为100、010、001的类型作为网络的输出，建立特征参数与霉变等级之间的神经网络识别模式。试验结果表明，该方法对正常花生仁、轻度霉变花生仁、严重霉变花生仁的检测准确率分别为95%、90%、100%，得到了较好的识别效果。     

计算机控制的农产品光特性检测系统

介绍了新建立的多功能农产品品质光特性无损检测系统,可由微机控制进行光谱数据的采集和分析,能迅速而准确地得到检测对象的反射光谱和透射光谱。自行设计的软件能完成对光谱数据的平滑处理、计算反射率、透射率和颜色参数、求微分光谱以及回归分析等处理。     

厚度和重力分选稻谷籽粒的品质特性分析

为达到从稻谷籽粒厚度和密度大小来均匀化其品质的目的,对稻谷进行了厚度分选和厚度分选后再进行重力分选加工。结果表明,收获稻谷含水率小于20%后,含水率不同的籽粒无法通过厚度和重力分选加工获得;分选后稻谷籽粒厚度和密度越大,籽粒的加工品质、物理化学、特性糊化特性等都相对较优;同时稻谷籽粒的密度越大,其加工破碎率越低,所能承受的最大三点弯曲作用力越大。因此厚度和重力分选具有使稻谷籽粒按照其内部品质分级和品质均匀化的作用,增加稻谷籽粒的品质附加值。     

水果内部品质在线近红外分光检测装置及试验

阐述了近红外分光法检测水果内部品质的基本原理和检测流程，分析比较了在线式反射光测定法、不完全遮光型透过光测定法和完全遮光型透过光测定法的特点；以柑橘和苹果为检测对象，用完全遮光型透过光水果内部品质测定装置进行在线糖度、酸度及内部褐变等检测试验，并与常规分析法测定结果进行回归分析。结果表明，在线检测的糖度值与实测值的相关系数在0.95以上，酸度相关系数大于0.85，且能检测内部缺陷，完全满足在线检测水果内部品质的要求。     

鸡蛋内部品质的光特性无损检测

无损检测鸡蛋内部品质是鸡蛋流通、加工中不可缺少的组成部分。为了提高鸡蛋内部品质光特性无损检测的精度,建立了鸡蛋的光学模型,找出了整蛋、内容物、蛋壳三者透射特性之间的关系。通过试验研究,得到了鸡蛋内部品质指标(哈氏单位)与整蛋透射率、蛋壳颜色、鸡蛋几何参数之间的相关关系。并对光特性无损检测的分级精度作了初步分析。     

基于同心轴圆筒式电容传感器的花生仁水分无损检测技术

为了实现花生仁含水率的快速准确检测,设计了以MSP430单片机为控制芯片的花生仁含水率检测仪,利用圆筒式电容传感器、温度传感器和称质量传感器分别检测花生仁的电容、温度和容积密度,通过信号检测调理电路进行测量信号电容到频率的转换,单片机进行数据处理后计算出花生仁含水率,在液晶屏上显示检测结果,并将检测数据存储到内存卡中。进一步研究了含水率、温度和容积密度对频率的影响规律,建立了描述含水率与差频、温度的数学模型,并验证了基于电容法检测花生含水率的可行性和模型的可靠性。试验表明,在含水率6.4%~18.2%、温度10~40℃范围内,该检测仪的测量相对误差绝对值小于0.5%。该研究为快速无损检测花生仁含水率提供了参考。     

评价大米储藏品质的炊饭特性指标的研究

提出了评价大米储藏品质的炊饭特性新指标——光透过率差。实验证明，随着大米品质的劣化，光透过率差明显变小。以此指标为主，结合原有的加热吸水率和ｐＨ值，对因生霉和陈化引起的大米储藏品质的变化，都能较好地进行评价。同时对影响这些指标稳定的实验因素也进行了探讨。     

农产品声学特性及其在品质无损检测中的应用

综述了国外对农产品声学特性研究的进展，阐明了农产品声学特性的测定原理，介绍了农产品声学特性在农产品品质无损检测中的典型应用实例，为发展我国农产品品质无损检测技术提供一定的参考。     

苹果内部品质自动化无损检测系统的原理与实现

介绍了一个苹果内部品质自动检测系统的原理性样机，该样机在计算机控制下基于介电特性实现苹果品质检测。待检测苹果的介电参数通过两只电容传感器和LCR(电感-电容-电阻)测量仪进行采样并输入样机内的控制计算机。选择等效电容(介电参数之一)作为苹果等级分类变量。对于一批待检测的苹果，其最佳分类阈值可通过对抽选出的合格和等外样本的在线学习获得。试验结果表明，该样机可获得良好的分类效果。在待检苹果直径为7.0 cm～8.5 cm，坏损部分的直径大于2 cm，电容传感器工作频率为1 kHz时，以学习得到的最佳分类阈值进行分类，分级正确率大于80%，分级效率达到2.5 s分选一个苹果，接近人工分选效率。     

原料及制油工艺对花生毛油中塑化剂含量的影响

为了探究油料品质及制油工艺对花生毛油中邻苯二甲酸酯类塑化剂(phthalatic acid esters,PAEs)的影响规律,对未脱皮花生仁和脱皮花生仁分别采用压榨法和浸出法提取花生毛油,对未脱皮和脱皮花生仁及其对应毛油中PAEs含量进行检测分析,研究原料品质和制油工艺对花生毛油中PAEs含量的影响。结果表明:未脱皮和脱皮花生仁中均含有PAEs且在制油过程向毛油中迁移和富集,在不同制油工艺中迁移率的差别致使不同毛油中PAEs含量也有明显差别。7个未脱皮花生仁样品中邻苯二甲酸二丁酯(dibutyl phthalate,DBP)、邻苯二甲酸二(2-乙基)己酯(di(2-ethtlhexyl)phthalate,DEHP)、邻苯二甲酸二异壬酯(diisononyl ortho-phthalate,DINP)和8种塑化剂总的(total content of 8 PAEs,∑8PAEs)质量分数分别为0.085~0.540、0.325~1.372、0.422~0.771和0.964~3.403 mg/kg。花生浸出毛油中DBP、DEHP、DINP及∑8PAEs平均含量是压榨毛油的1.39、1.23、1.16、1.22倍。花生仁脱皮制油可使毛油中DBP、DEHP、DINP、∑8PAEs含量分别降低33.0%~36.4%、26.7%~29.4%、15.0%~18.7%、22.5%~23.0%。在花生油生产尤其是炒香型花生油生产时,严格对花生仁原料中PAEs含量进行监控,同时采用花生脱皮压榨取油,对花生油产品的PAEs风险防范和控制有重要意义。研究结果可为企业生产高品质花生油,降低PAEs风险提供参考。     

收获时期及干燥方式对花生品质的影响

为探索不同收获期和后熟干燥方式对花生品质的影响,该研究以泰花5号花生为试验对象,采用在株晾干法、鲜摘晾干法、鲜摘催干法3种方法对3个时期收获的花生进行后熟干燥品质对比测试分析。结果表明,在同一收获期中,在株晾干法花生百果质量、百仁质量显著高于其他2种方法,该后熟干燥方法的增重作用随收获期提前而更明显(P0.05);但在相同后熟干燥方法中,提前2周收获的干燥荚果百果质量、百仁质量均显著低于前1周和原定收期收获的花生荚果(P0.05)。自然晾晒干燥期间,在株晾干花生果壳、果仁含水率均高于同期鲜摘晾干果壳、果仁含水率,两种晾干方式含水率差异在初期逐渐增加、随后逐渐减小直至达到相当的最终含水率。鲜摘晾干和鲜摘催干果仁粗蛋白、粗脂肪均未见显著差异(P0.05),而在株晾干果仁粗蛋白、粗脂肪含量分别增加了3%、2%左右;而收获期越早,果仁粗蛋白和粗脂肪含量越低。在果仁不饱和脂肪酸总相对含量上,鲜摘晾干、在株晾干果仁与新鲜果仁未见差异(P0.05),但机械催干果仁显著低于新鲜果仁(P0.05)。在果仁氨基酸组成方面,经3种不同后熟干燥方法后,8种主要氨基酸及氨基酸总含量均呈现在株晾干含量最高、鲜摘晾干其次、机械催干最低的差异(P0.05)。在株晾干花生果柄横断面显微结构观察表明,果柄在干燥初期仍保留对水分、养分等物质输导、贮藏的空间通道,为荚果的物质代谢和积累提供必要条件。该研究结果为花生生产实践提供参考。     

超声复合酸处理促进花生分离蛋白的亚基解离

为了改善蛋白质的功能特性,该研究分析了超声复合酸处理对花生分离蛋白的溶解性、紫外光谱、荧光光谱、二级结构及纳米结构等的影响,并探讨不同处理条件下蛋白聚集体结构变化的机理。结果表明,超声作用可以明显促进花生分离蛋白的不溶性聚集体向可溶性聚集体转变,单独超声及超声复合酸处理使其溶解度相对于对照分别增加了12.9%和15.3%（P<0.05）;电泳、紫外和荧光光谱表明,超声和酸作用均有助于亚基解离及蛋白质结构展开,从而促进更多的酪氨酸、色氨酸和苯丙氨酸等疏水性基团暴露;圆二色谱分析显示,与对照相比,在超声复合酸处理使花生分离蛋白的a-螺旋增加21.9%,β-折叠减少3.6%,无规则卷曲增加1.8%（P<0.05）;纳米结构表明,超声复合酸处理最大程度地降低了花生分离蛋白的颗粒大小。该研究证实,在酸性条件下进行超声处理,能显著促进花生分离蛋白的亚基解离和结构展开。该研究为后期蛋白亚基重新相互作用形成不同功能的改性蛋白提供参考。     

Effects of long-term fertilizer applications on peanut yield and quality and plant and soil heavy metal accumulation

The status of essential and potentially toxic trace elements in soils and crops can be affected by long-term fertilization practices. This study aimed to investigate changes in peanut (Arachis hypogaea L.) yield and kernel quality, and changes in copper (Cu), zinc (Zn), lead (Pb), and cadmium (Cd) concentrations in soil and peanut kernels after 16 years of continuous cropping with different fertilization treatments. Five fertilization treatments were applied at a red soil site in Southeast China:chemical fertilizer (F) containing nitrogen, phosphorus, and potassium, F + trace elements (FT), pig manure (M), M + effective microorganisms (MB), and MB + trace elements (MBT). Properties of soil and pig manure, heavy metal contents in soil and peanut kernels, and the compositions of amino and fatty acids in kernels were determined. Application of pig manure significantly increased peanut biomass, kernel yield, and crude protein and total amino acid contents in kernels, but led to higher amounts of Cu, Zn, and Cd in soil and higher amounts of Zn and Cd in peanut kernels compared with that of chemical fertilizer. There should be greater concern about potential kernel Cd and Zn contaminations resulting from long-term application of pig manure contaminated with potentially toxic metals as an organic fertilizer.     

Detecting Vitreous Wheat Kernels Using Reflectance and Transmittance Image Analysis

The proportion of vitreous durum kernels in a sample is an important grading attribute in assessing the quality of durum wheat. The current standard method of determining wheat vitreousness is performed by visual inspection, which can be tedious and subjective. The objective of this study was to evaluate an automated machine‐vision inspection system to detect wheat vitreousness using reflectance and transmittance images. Two subclasses of durum wheat were investigated in this study: hard and vitreous of amber color (HVAC) and not hard and vitreous of amber color (NHVAC). A total of 4,907 kernels in the calibration set and 4,407 kernels in the validation set were imaged using a Cervitec 1625 grain inspection system. Classification models were developed with stepwise discriminant analysis and an artificial neural network (ANN). A discriminant model correctly classified 94.9% of the HVAC and 91.0% of the NHVAC in the calibration set, and 92.4% of the HVAC and 92.7% of the NHVAC in the validation set. The classification results using the ANN were not as good as with the discriminant methods, but the ANN only used features from reflectance images. Among all the kernels, mottled kernels were the most difficult to classify. Both reflectance and transmittance images were helpful in classification. In conclusion, the Cervitec 1625 automated visionbased wheat quality inspection system may provide the grain industry with a rapid, objective, and accurate method to determine the vitreousness of durum wheat.     

Reduction of Aflatoxin and Fumonisin Contamination in Yellow Corn by High‐Speed Dual‐Wavelength Sorting

A high‐speed dual‐wavelength sorter was tested for removing corn contaminated in the field with aflatoxin and fumonisin. To achieve accurate sorting, single kernel reflectance spectra (500–1,700 nm) were analyzed to select the optimal pair of optical filters to detect mycotoxin‐contaminated corn during high‐speed sorting. A routine, based on discriminant analysis, was developed to select the two absorbance bands in the spectra that would give the greatest classification accuracy. In a laboratory setting, and with the kernels stationary, absorbances at 750 and 1,200 nm could correctly identify >99% of the kernels as aflatoxin‐contaminated (>100 ppb) or uncontaminated. A high‐speed sorter was tested using the selected filter pair for corn samples inoculated with Aspergillus flavus; naturally infested corn grown in central Illinois; and naturally infested, commercially grown and harvested corn from eastern Kansas (2002 harvest). For the Kansas corn, the sorter was able to reduce aflatoxin levels by 81% from an initial average of 53 ppb, while fumonisin levels in the same grain samples were reduced an average of 85% from an initial level of 17 ppm. Similar reductions in mycotoxin levels were observed after high‐speed sorting of A. flavus inoculated and naturally mold‐infested corn grown in Illinois.     

Reflectance and Transmittance Spectroscopy Applied to Detecting Fumonisin in Single Corn Kernels Infected with Fusarium verticillioides

Reflectance and transmittance visible and near‐infrared spectroscopy were used to detect fumonisin in single corn kernels infected with Fusarium verticillioides. Kernels with >100 ppm and <10 ppm could be classed accurately as fumonisin positive or negative, respectively. Classification results were generally better for oriented kernels than for kernels that were randomly placed in the spectrometer viewing area. Generally, models based on reflectance spectra have higher correct classification than models based on transmittance spectra. Statistical analyses indicated that including near‐infrared wavelengths in calibrations improved classifications, and some calibrations were improved by including visible wavelengths. Thus, the color and chemical constituents of the infected kernel contribute to classification models. These results show that this technology can be used to rapidly and nondestructively screen single corn kernels for the presence of fumonisin, and may be adaptable to on‐line detection and sorting.     

Protein Content of Bulk Wheat from Near‐Infrared Reflectance of Individual Kernels

Protein content of wheat by near‐infrared (NIR) reflectance of bulk samples is routinely practiced. New instrumentation that permits automated NIR analysis of individual kernels is now available, with the potential for rapid NIR‐based determinations of color, disease, and protein content, all on a single kernel (sk) basis. In the event that the protein content of the bulk sample is needed rather than that of the individual kernels, the present study examines the feasibility of estimating bulk sample protein from sk spectral readings. On the basis of 318 wheat samples of 10 kernels per sample, encompassing five U.S. wheat classes, the study demonstrates that with as few as 300 kernels bulk sample protein content may be estimated by sk NIR reflectance spectra at an accuracy equivalent to conventional bulk kernel NIR instrumentation.     

种植至储藏期花生黄曲霉毒素B_1污染研究

为解析种植至储藏期花生受黄曲霉侵染及黄曲霉毒素B1(AFB_1)污染的规律,揭示花生AFB_1污染的源头及主要影响因素,选取种植湛红2号和湛油75的花生田,采集种植期花生果和土壤及储藏1~4个月的花生果,分析花生和土壤真菌菌相,并采用高效液相色谱法测定花生AFB_1含量。结果表明,种植期黄曲霉侵染花生果主要发生在成熟期,但黄曲霉污染率均在8%以下;湛油75花生田土壤黄曲霉菌落数显著低于湛红2号,但花生果黄曲霉污染率显著高于湛红2号,表明湛红2号具有一定的黄曲霉抗性;湛油75和湛红2号分别在110 d和120 d检测到AFB_1,含量分别为3.37μg·kg~(-1)和2.08μg·kg~(-1),表明花生黄曲霉毒素含量与污染率呈正相关。储藏期花生果中未检测到黄曲霉和AFB_1,这主要是由于花生晾晒后水活度(aw)降低至0.70以下,不适合黄曲霉生长繁殖和毒素生物合成。综上,黄曲霉在荚果成熟期开始侵染花生果导致产生AFB_1,而储藏期保持较低的aw可有效预防黄曲霉及AFB_1污染。本研究结果为制定种植至储藏期花生黄曲霉毒素全程防控措施提供了理论依据。     

花生根和荚果对外源钙的吸收特性研究

为了明确花生根和荚果对外源钙的吸收特性,本研究选取对钙敏感性不同的豫花37和豫花23为试材,利用自主研发的花生根果分区培养装置开展试验,设置不施钙(CK)、根区施0.20 g·kg^-1CaO(RL)、根区施0.80 g·kg^-1 CaO(RH)、荚果区施0.20 g·kg^-1CaO(PL)、荚果区施0.80 g·kg^-1 CaO(PH)共5个处理,探究根区和荚果区不同外源钙处理对土壤钙含量、花生生长发育及产质量、钙吸收积累分配特征的影响。结果表明,饱果成熟期,同一基因型花生根区施钙土壤钙含量低于荚果区相同施钙量处理,且以酸溶态钙为主,占土壤全钙的37.97%~64.52%;与根区施钙相比,荚果区施相同量的外源钙提高了花生的饱果数、出仁率和荚果产量,降低了籽仁可溶性糖含量,增加了油酸/亚油酸比值(O/L)和粗蛋白、粗脂肪、蛋氨酸、赖氨酸的含量;根区施钙花生根茎叶的吸钙量占花生植株总吸钙量的87.39%~91.11%,果壳和籽仁占8.89%~12.61%,荚果区施钙花生根茎叶占74.10%~84.85%,果壳和籽仁占15.15%~25.90%;与根区施钙相比,荚果区施钙显著提高了钙利用效率,豫花37荚果和籽仁钙利用效率分别提高了42.35%~49.28%和37.73%~43.89%,豫花23分别提高了32.43%~46.17%和21.05%~47.09%。总体来看,荚果区施钙较根区施钙显著提高了花生产质量和钙的利用效率。本研究结果为指导花生钙肥施用提供了理论依据。